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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Conversion From The Korean Dementia Screening Questionnaire To The Informant Questionnaire On Cognitive Decline In
Tae Young Yeo1, Keonyeup Kim1, Moon Ho Park1
1Department of Neurology, Korea University Ansan Hospital, Ansan, Republic of Korea.
Purpose:
The ability to convert scores between cognitive measurements would facilitate the longitudinal assessment of cognition in clinical practice and the comparison and synthesis of cognitive data from international, multicenter, or longitudinal studies. The primary aim of this study was to apply a simple and reliable method for converting scores from the Korean Dementia Screening Questionnaire (KDSQ) to those of the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE).
Patients And Methods:
A total of 627 participants, with and without cognitive dysfunction, received both the KDSQ and the IQCODE at the same visit. The scores of both tools were calculated, and equipercentile equating was used to create a method for converting scores from the KDSQ to the IQCODE.
Results:
KDSQ scores were highly correlated with IQCODE scores (Pearson r = 0.905, P < 0.01). We developed scores for converting the KDSQ to the IQCODE using equipercentile equating and log-linear smoothing. We provide an easy-to-use table that enables the conversion of KDSQ scores to IQCODE scores.
Conclusion:
We delivered a simple and reliable method for converting scores from the KDSQ to the IQCODE. The conversion score table reported here enables direct and easy comparison of these cognitive measurements in older adults.
